Pandas Profiling Report

Dataset statistics

Number of variables	16
Number of observations	45211
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	5.5 MiB
Average record size in memory	128.0 B

Variable types

Numeric	8
Categorical	8

Alerts

`month` is highly overall correlated with `housing` and 3 other fields	High correlation
`pdays` is highly overall correlated with `month` and 1 other fields	High correlation
`previous` is highly overall correlated with `pdays` and 1 other fields	High correlation
`housing` is highly overall correlated with `month`	High correlation
`contact` is highly overall correlated with `month`	High correlation
`poutcome` is highly overall correlated with `pdays`	High correlation
`day` is highly overall correlated with `month`	High correlation
`previous` is highly skewed (γ1 = 41.84645447)	Skewed
`balance` has 3514 (7.8%) zeros	Zeros
`previous` has 36954 (81.7%) zeros	Zeros

Reproduction

Analysis started	2022-12-05 13:36:57.728840
Analysis finished	2022-12-05 13:37:14.391912
Duration	16.66 seconds
Software version	pandas-profiling vv3.5.0
Download configuration	config.json

age
Real number (ℝ)

Distinct	77
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	40.93621

Minimum	18
Maximum	95
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	353.3 KiB

Quantile statistics

Minimum	18
5-th percentile	27
Q1	33
median	39
Q3	48
95-th percentile	59
Maximum	95
Range	77
Interquartile range (IQR)	15

Descriptive statistics

Standard deviation	10.618762
Coefficient of variation (CV)	0.25939778
Kurtosis	0.31957038
Mean	40.93621
Median Absolute Deviation (MAD)	7
Skewness	0.68481793
Sum	1850767
Variance	112.75811
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
32	2085	4.6%
31	1996	4.4%
33	1972	4.4%
34	1930	4.3%
35	1894	4.2%
36	1806	4.0%
30	1757	3.9%
37	1696	3.8%
39	1487	3.3%
38	1466	3.2%
Other values (67)	27122	60.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
18	12	< 0.1%
19	35	0.1%
20	50	0.1%
21	79	0.2%
22	129	0.3%
23	202	0.4%
24	302	0.7%
25	527	1.2%
26	805	1.8%
27	909	2.0%

Value	Count	Frequency (%)
95	2	< 0.1%
94	1	< 0.1%
93	2	< 0.1%
92	2	< 0.1%
90	2	< 0.1%
89	3	< 0.1%
88	2	< 0.1%
87	4	< 0.1%
86	9	< 0.1%
85	5	< 0.1%

marital
Categorical

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	353.3 KiB

1	27214
0	12790
2	5207

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	45211
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	0
3rd row	1
4th row	1
5th row	0

Common Values

Value	Count	Frequency (%)
1	27214	60.2%
0	12790	28.3%
2	5207	11.5%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
1	27214	60.2%
0	12790	28.3%
2	5207	11.5%

Most occurring characters

Value	Count	Frequency (%)
1	27214	60.2%
0	12790	28.3%
2	5207	11.5%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	45211	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	27214	60.2%
0	12790	28.3%
2	5207	11.5%

Most occurring scripts

Value	Count	Frequency (%)
Common	45211	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	27214	60.2%
0	12790	28.3%
2	5207	11.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	45211	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	27214	60.2%
0	12790	28.3%
2	5207	11.5%

education
Categorical

Distinct	4
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	353.3 KiB

2	23202
3	13301
1	6851
0	1857

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	45211
Distinct characters	4
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	3
2nd row	2
3rd row	2
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
2	23202	51.3%
3	13301	29.4%
1	6851	15.2%
0	1857	4.1%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
2	23202	51.3%
3	13301	29.4%
1	6851	15.2%
0	1857	4.1%

Most occurring characters

Value	Count	Frequency (%)
2	23202	51.3%
3	13301	29.4%
1	6851	15.2%
0	1857	4.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	45211	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
2	23202	51.3%
3	13301	29.4%
1	6851	15.2%
0	1857	4.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	45211	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
2	23202	51.3%
3	13301	29.4%
1	6851	15.2%
0	1857	4.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	45211	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
2	23202	51.3%
3	13301	29.4%
1	6851	15.2%
0	1857	4.1%

default
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	353.3 KiB

0	44396
1	815

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	45211
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	44396	98.2%
1	815	1.8%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
0	44396	98.2%
1	815	1.8%

Most occurring characters

Value	Count	Frequency (%)
0	44396	98.2%
1	815	1.8%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	45211	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	44396	98.2%
1	815	1.8%

Most occurring scripts

Value	Count	Frequency (%)
Common	45211	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	44396	98.2%
1	815	1.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	45211	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	44396	98.2%
1	815	1.8%

balance
Real number (ℝ)

Distinct	7168
Distinct (%)	15.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1362.2721

Minimum	-8019
Maximum	102127
Zeros	3514
Zeros (%)	7.8%
Negative	3766
Negative (%)	8.3%
Memory size	353.3 KiB

Quantile statistics

Minimum	-8019
5-th percentile	-172
Q1	72
median	448
Q3	1428
95-th percentile	5768
Maximum	102127
Range	110146
Interquartile range (IQR)	1356

Descriptive statistics

Standard deviation	3044.7658
Coefficient of variation (CV)	2.2350644
Kurtosis	140.75155
Mean	1362.2721
Median Absolute Deviation (MAD)	448
Skewness	8.3603083
Sum	61589682
Variance	9270599
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	3514	7.8%
1	195	0.4%
2	156	0.3%
4	139	0.3%
3	134	0.3%
5	113	0.2%
6	88	0.2%
8	81	0.2%
23	75	0.2%
7	69	0.2%
Other values (7158)	40647	89.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
-8019	1	< 0.1%
-6847	1	< 0.1%
-4057	1	< 0.1%
-3372	1	< 0.1%
-3313	1	< 0.1%
-3058	1	< 0.1%
-2827	1	< 0.1%
-2712	1	< 0.1%
-2604	1	< 0.1%
-2282	1	< 0.1%

Value	Count	Frequency (%)
102127	1	< 0.1%
98417	1	< 0.1%
81204	2	< 0.1%
71188	1	< 0.1%
66721	1	< 0.1%
66653	1	< 0.1%
64343	1	< 0.1%
59649	1	< 0.1%
58932	1	< 0.1%
58544	1	< 0.1%

housing
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	353.3 KiB

1	25130
0	20081

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	45211
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	0

Common Values

Value	Count	Frequency (%)
1	25130	55.6%
0	20081	44.4%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
1	25130	55.6%
0	20081	44.4%

Most occurring characters

Value	Count	Frequency (%)
1	25130	55.6%
0	20081	44.4%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	45211	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	25130	55.6%
0	20081	44.4%

Most occurring scripts

Value	Count	Frequency (%)
Common	45211	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	25130	55.6%
0	20081	44.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	45211	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	25130	55.6%
0	20081	44.4%

loan
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	353.3 KiB

0	37967
1	7244

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	45211
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	1
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	37967	84.0%
1	7244	16.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
0	37967	84.0%
1	7244	16.0%

Most occurring characters

Value	Count	Frequency (%)
0	37967	84.0%
1	7244	16.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	45211	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	37967	84.0%
1	7244	16.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	45211	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	37967	84.0%
1	7244	16.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	45211	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	37967	84.0%
1	7244	16.0%

contact
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	353.3 KiB

1	32191
0	13020

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	45211
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
1	32191	71.2%
0	13020	28.8%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
1	32191	71.2%
0	13020	28.8%

Most occurring characters

Value	Count	Frequency (%)
1	32191	71.2%
0	13020	28.8%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	45211	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	32191	71.2%
0	13020	28.8%

Most occurring scripts

Value	Count	Frequency (%)
Common	45211	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	32191	71.2%
0	13020	28.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	45211	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	32191	71.2%
0	13020	28.8%

day
Real number (ℝ)

Distinct	31
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	15.806419

Minimum	1
Maximum	31
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	353.3 KiB

Quantile statistics

Minimum	1
5-th percentile	3
Q1	8
median	16
Q3	21
95-th percentile	29
Maximum	31
Range	30
Interquartile range (IQR)	13

Descriptive statistics

Standard deviation	8.3224762
Coefficient of variation (CV)	0.52652509
Kurtosis	-1.0598974
Mean	15.806419
Median Absolute Deviation (MAD)	7
Skewness	0.093079014
Sum	714624
Variance	69.263609
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=31)

Value	Count	Frequency (%)
20	2752	6.1%
18	2308	5.1%
21	2026	4.5%
17	1939	4.3%
6	1932	4.3%
5	1910	4.2%
14	1848	4.1%
8	1842	4.1%
28	1830	4.0%
7	1817	4.0%
Other values (21)	25007	55.3%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	322	0.7%
2	1293	2.9%
3	1079	2.4%
4	1445	3.2%
5	1910	4.2%
6	1932	4.3%
7	1817	4.0%
8	1842	4.1%
9	1561	3.5%
10	524	1.2%

Value	Count	Frequency (%)
31	643	1.4%
30	1566	3.5%
29	1745	3.9%
28	1830	4.0%
27	1121	2.5%
26	1035	2.3%
25	840	1.9%
24	447	1.0%
23	939	2.1%
22	905	2.0%

month
Real number (ℝ)

Distinct	12
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	6.1446551

Minimum	1
Maximum	12
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	353.3 KiB

Quantile statistics

Minimum	1
5-th percentile	2
Q1	5
median	6
Q3	8
95-th percentile	11
Maximum	12
Range	11
Interquartile range (IQR)	3

Descriptive statistics

Standard deviation	2.408034
Coefficient of variation (CV)	0.39189083
Kurtosis	0.048579
Mean	6.1446551
Median Absolute Deviation (MAD)	1
Skewness	0.24284195
Sum	277806
Variance	5.7986276
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=12)

Value	Count	Frequency (%)
5	13766	30.4%
7	6895	15.3%
8	6247	13.8%
6	5341	11.8%
11	3970	8.8%
4	2932	6.5%
2	2649	5.9%
1	1403	3.1%
10	738	1.6%
9	579	1.3%
Other values (2)	691	1.5%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	1403	3.1%
2	2649	5.9%
3	477	1.1%
4	2932	6.5%
5	13766	30.4%
6	5341	11.8%
7	6895	15.3%
8	6247	13.8%
9	579	1.3%
10	738	1.6%

Value	Count	Frequency (%)
12	214	0.5%
11	3970	8.8%
10	738	1.6%
9	579	1.3%
8	6247	13.8%
7	6895	15.3%
6	5341	11.8%
5	13766	30.4%
4	2932	6.5%
3	477	1.1%

duration
Real number (ℝ)

Distinct	1573
Distinct (%)	3.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	258.16308

Minimum	0
Maximum	4918
Zeros	3
Zeros (%)	< 0.1%
Negative	0
Negative (%)	0.0%
Memory size	353.3 KiB

Quantile statistics

Minimum	0
5-th percentile	35
Q1	103
median	180
Q3	319
95-th percentile	751
Maximum	4918
Range	4918
Interquartile range (IQR)	216

Descriptive statistics

Standard deviation	257.52781
Coefficient of variation (CV)	0.99753928
Kurtosis	18.153915
Mean	258.16308
Median Absolute Deviation (MAD)	93
Skewness	3.1443181
Sum	11671811
Variance	66320.574
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
124	188	0.4%
90	184	0.4%
89	177	0.4%
104	175	0.4%
122	175	0.4%
114	175	0.4%
136	174	0.4%
139	174	0.4%
112	174	0.4%
121	173	0.4%
Other values (1563)	43442	96.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	3	< 0.1%
1	2	< 0.1%
2	3	< 0.1%
3	4	< 0.1%
4	15	< 0.1%
5	35	0.1%
6	45	0.1%
7	73	0.2%
8	85	0.2%
9	77	0.2%

Value	Count	Frequency (%)
4918	1	< 0.1%
3881	1	< 0.1%
3785	1	< 0.1%
3422	1	< 0.1%
3366	1	< 0.1%
3322	1	< 0.1%
3284	1	< 0.1%
3253	1	< 0.1%
3183	1	< 0.1%
3102	1	< 0.1%

campaign
Real number (ℝ)

Distinct	48
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2.7638407

Minimum	1
Maximum	63
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	353.3 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	2
Q3	3
95-th percentile	8
Maximum	63
Range	62
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	3.0980209
Coefficient of variation (CV)	1.1209115
Kurtosis	39.249651
Mean	2.7638407
Median Absolute Deviation (MAD)	1
Skewness	4.8986502
Sum	124956
Variance	9.5977334
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=48)

Value	Count	Frequency (%)
1	17544	38.8%
2	12505	27.7%
3	5521	12.2%
4	3522	7.8%
5	1764	3.9%
6	1291	2.9%
7	735	1.6%
8	540	1.2%
9	327	0.7%
10	266	0.6%
Other values (38)	1196	2.6%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	17544	38.8%
2	12505	27.7%
3	5521	12.2%
4	3522	7.8%
5	1764	3.9%
6	1291	2.9%
7	735	1.6%
8	540	1.2%
9	327	0.7%
10	266	0.6%

Value	Count	Frequency (%)
63	1	< 0.1%
58	1	< 0.1%
55	1	< 0.1%
51	1	< 0.1%
50	2	< 0.1%
46	1	< 0.1%
44	1	< 0.1%
43	3	< 0.1%
41	2	< 0.1%
39	1	< 0.1%

pdays
Real number (ℝ)

Distinct	559
Distinct (%)	1.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	40.197828

Minimum	-1
Maximum	871
Zeros	0
Zeros (%)	0.0%
Negative	36954
Negative (%)	81.7%
Memory size	353.3 KiB

Quantile statistics

Minimum	-1
5-th percentile	-1
Q1	-1
median	-1
Q3	-1
95-th percentile	317
Maximum	871
Range	872
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	100.12875
Coefficient of variation (CV)	2.4908994
Kurtosis	6.9351952
Mean	40.197828
Median Absolute Deviation (MAD)	0
Skewness	2.6157155
Sum	1817384
Variance	10025.766
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
-1	36954	81.7%
182	167	0.4%
92	147	0.3%
91	126	0.3%
183	126	0.3%
181	117	0.3%
370	99	0.2%
184	85	0.2%
364	77	0.2%
95	74	0.2%
Other values (549)	7239	16.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
-1	36954	81.7%
1	15	< 0.1%
2	37	0.1%
3	1	< 0.1%
4	2	< 0.1%
5	11	< 0.1%
6	10	< 0.1%
7	7	< 0.1%
8	25	0.1%
9	12	< 0.1%

Value	Count	Frequency (%)
871	1	< 0.1%
854	1	< 0.1%
850	1	< 0.1%
842	1	< 0.1%
838	1	< 0.1%
831	1	< 0.1%
828	1	< 0.1%
826	1	< 0.1%
808	1	< 0.1%
805	1	< 0.1%

previous
Real number (ℝ)

HIGH CORRELATION
SKEWED
ZEROS

Distinct	41
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.58032337

Minimum	0
Maximum	275
Zeros	36954
Zeros (%)	81.7%
Negative	0
Negative (%)	0.0%
Memory size	353.3 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	3
Maximum	275
Range	275
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	2.303441
Coefficient of variation (CV)	3.9692371
Kurtosis	4506.8607
Mean	0.58032337
Median Absolute Deviation (MAD)	0
Skewness	41.846454
Sum	26237
Variance	5.3058406
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=41)

Value	Count	Frequency (%)
0	36954	81.7%
1	2772	6.1%
2	2106	4.7%
3	1142	2.5%
4	714	1.6%
5	459	1.0%
6	277	0.6%
7	205	0.5%
8	129	0.3%
9	92	0.2%
Other values (31)	361	0.8%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	36954	81.7%
1	2772	6.1%
2	2106	4.7%
3	1142	2.5%
4	714	1.6%
5	459	1.0%
6	277	0.6%
7	205	0.5%
8	129	0.3%
9	92	0.2%

Value	Count	Frequency (%)
275	1	< 0.1%
58	1	< 0.1%
55	1	< 0.1%
51	1	< 0.1%
41	1	< 0.1%
40	1	< 0.1%
38	2	< 0.1%
37	2	< 0.1%
35	1	< 0.1%
32	1	< 0.1%

poutcome
Categorical

Distinct	4
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	353.3 KiB

0	36959
2	4901
3	1840
1	1511

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	45211
Distinct characters	4
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	36959	81.7%
2	4901	10.8%
3	1840	4.1%
1	1511	3.3%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
0	36959	81.7%
2	4901	10.8%
3	1840	4.1%
1	1511	3.3%

Most occurring characters

Value	Count	Frequency (%)
0	36959	81.7%
2	4901	10.8%
3	1840	4.1%
1	1511	3.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	45211	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	36959	81.7%
2	4901	10.8%
3	1840	4.1%
1	1511	3.3%

Most occurring scripts

Value	Count	Frequency (%)
Common	45211	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	36959	81.7%
2	4901	10.8%
3	1840	4.1%
1	1511	3.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	45211	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	36959	81.7%
2	4901	10.8%
3	1840	4.1%
1	1511	3.3%

Target
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	353.3 KiB

0	39922
1	5289

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	45211
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	39922	88.3%
1	5289	11.7%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
0	39922	88.3%
1	5289	11.7%

Most occurring characters

Value	Count	Frequency (%)
0	39922	88.3%
1	5289	11.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	45211	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	39922	88.3%
1	5289	11.7%

Most occurring scripts

Value	Count	Frequency (%)
Common	45211	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	39922	88.3%
1	5289	11.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	45211	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	39922	88.3%
1	5289	11.7%

Auto

The auto setting is an interpretable pairwise column metric of the following mapping:

Variable_type-Variable_type : Method, Range
Categorical-Categorical : Cramer's V, [0,1]
Numerical-Categorical : Cramer's V, [0,1] (using a discretized numerical column)
Numerical-Numerical : Spearman's ρ, [-1,1]

The number of bins used in the discretization for the Numerical-Categorical column pair can be changed using config.correlations["auto"].n_bins. The number of bins affects the granularity of the association you wish to measure.

This configuration uses the recommended metric for each pair of columns.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Count
Matrix

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

First rows
Last rows

	age	marital	education	default	balance	housing	loan	day	month	duration	campaign	pdays
0	58	1	3	0	2143	1	0	5	5	261	1	-1
1	44	0	2	0	29	1	0	5	5	151	1	-1
2	33	1	2	0	2	1	1	5	5	76	1	-1
3	47	1	0	0	1506	1	0	5	5	92	1	-1
4	33	0	0	0	1	0	0	5	5	198	1	-1
5	35	1	3	0	231	1	0	5	5	139	1	-1
6	28	0	3	0	447	1	1	5	5	217	1	-1
7	42	2	3	1	2	1	0	5	5	380	1	-1
8	58	1	1	0	121	1	0	5	5	50	1	-1
9	43	0	2	0	593	1	0	5	5	55	1	-1

	age	marital	education	balance	loan	contact	day	month	duration	campaign	pdays	previous	poutcome	Target
45201	53	1	3	583	0	1	17	11	226	1	184	4	1	1
45202	34	0	2	557	0	1	17	11	224	1	-1	0	0	1
45203	23	0	3	113	0	1	17	11	266	1	-1	0	0	1
45204	73	1	2	2850	0	1	17	11	300	1	40	8	2	1
45205	25	0	2	505	1	1	17	11	386	2	-1	0	0	1
45206	51	1	3	825	0	1	17	11	977	3	-1	0	0	1
45207	71	2	1	1729	0	1	17	11	456	2	-1	0	0	1
45208	72	1	2	5715	0	1	17	11	1127	5	184	3	1	1
45209	57	1	2	668	0	1	17	11	508	4	-1	0	0	0
45210	37	1	2	2971	0	1	17	11	361	2	188	11	3	0

Overview

Variables

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII